Conformers

ACONFL

Summary

Performance in predicting relative conformer energies of 12 C12H26, 16 C16H34 and 20 C20H42 conformers. Reference data from PNO-LCCSD(T)-F12/ AVQZ calculations.

Metrics

  1. Conformer energy error

For each complex, the the relative energy is calculated by taking the difference in energy between the given conformer and the reference (zero-energy) conformer. This is compared to the reference conformer energy, calculated in the same way.

Computational cost

Low: tests are likely to take minutes to run on CPU.

Data availability

Input structures:

  • Conformational Energy Benchmark for Longer n-Alkane Chains Sebastian Ehlert, Stefan Grimme, and Andreas Hansen The Journal of Physical Chemistry A 2022 126 (22), 3521-3535 DOI: 10.1021/acs.jpca.2c02439

Reference data:

  • Same as input data

  • \(PNO-LCCSD(T)-F12/ AVQZ\) level of theory: a local, explicitly correlated coupled cluster method.

Folmsbee

Summary

Performance in predicting relative conformer energies for a set of drug-like molecules. Each molecule has a small set of conformers (3-10 per molecule) whose energies are ranked relative to the lowest-energy conformer. Reference data from DLPNO-CCSD(T) calculations.

Metrics

For each molecule, the relative energy of every conformer is taken with respect to the lowest-energy reference conformer (set to zero). The predicted energies are aligned to the same reference conformer and converted to kcal/mol before being compared against the \(DLPNO-CCSD(T)\) reference.

  1. MAE

The mean absolute error between predicted and reference relative energies, averaged over all molecules.

  1. Conformer Score

For each molecule, the per-molecule MAE and RMSE are passed through a soft threshold (MAE at 0.5 kcal/mol, RMSE at 1.5 kcal/mol) to give a value between 0 and 1, and these are averaged across all molecules. Molecules for which the model fails to produce an energy profile score 0.

Computational cost

Medium: Minutes on GPU. Minutes to tens of minutes on CPU.

Data availability

Input structures:

  • Assessing conformer energies using electronic structure and machine learning methods Dakota Folmsbee, Geoffrey Hutchison International Journal of Quantum Chemistry 2020 121 (1) e26381 DOI: 10.1002/qua.26381

Reference data:

  • Same as input data

  • \(DLPNO-CCSD(T)\) level of theory: a local coupled-cluster method.